Ọnụego mmụta cyclical
Ọnụego mmụta cyclical na-agbagharị ugboro ugboro n'ịmụ ihe n'ogo elu na ala n'etiti oke ala na elu kama naanị ire ere.
Nchịkọta
This counterintuitive bouncing can speed up convergence and helps the optimizer escape sharp local minima and saddle points.
Ime miri emi
Leslie Smith tụpụtara na 2015, ọnụego mmụta cyclical (CLR) na-agbagha echiche ahụ na ọnụego ahụ kwesịrị ibelata naanị. Kama, ọ na-agbagharị n'etiti opekempe na nke kachasị karịa n'elu ọnụọgụ ịrị elu ('cycle'), na-enwekarị ọdịdị triangular. Echiche ahụ: iwelite ọnụego oge ụfọdụ na-enye ike nke na-eme ka ihe nlereanya ahụ si na ebe dara ogbenye, minima dị nkọ ma na-agafe ebe nchekwa, ebe obere usoro na-ahapụ ya ka ọ dozie. Smith webakwara 'Nnwale oke LR' - obere ọsọ nke na-ebuli ọnụego elu ka ọ na-ekiri ọnwụ - iji chọta oke oke na-akpaghị aka. Triangular, triangular-nwere ire ere, na amụma otu okirikiri a ma ama na-ewulite n'echiche a.
Nghọta nka nka
Atumatu triangular n'ahịrị na-abawanye ọnụego site na ntọala ruo ihe karịrị ọkara okirikiri, wee jiri ahịrị belata ya azụ karịa ọkara nke ọzọ. A na-edokarị ogologo okirikiri ahụ ka ọ bụrụ uru nrụgharị oge ole na ole. Amụma otu okirikiri na-eji otu okirikiri ogologo ogologo: ọnụego na-ebili wee daa n'okpuru mmalite, ebe ume na-aga n'ihu - elu mgbe ọnụego ahụ dị ala na nke ọzọ - nke na-arụ ọrụ dị ka onye na-ahazi ma na-eme ka 'mgbakọ dị elu' na ụfọdụ ọrụ.
Mmetụta atụmatụ
Ọnụ ego na mmefu ego
Mkpebi ihe owuwu ụlọ na-akwalite arụmọrụ yana ọnụ ahịa ọrụ ruo ọtụtụ afọ.
Mkpebi doro anya
Nkà mmụta nka na-enyere ndị otu egwuregwu aka ịhọrọ nchịkọta ziri ezi, ọ bụghị naanị nke kachasị ọhụrụ.
Quality akara
Nhọrọ injinia ka mma na-ebelata ihe omume ntụkwasị obi na mmepụta.
Ọdịnihu nke ọnụego mmụta cyclical
Usoro cyclical na amụma otu okirikiri ka na-ewu ewu maka ọzụzụ ngwa ngwa gbasara ọhụhụ na ọrụ tabular, na ule nso LR bụ aghụghọ nlegharị anya ọkọlọtọ. Maka ụdị asụsụ buru ibu, usoro ikpo ọkụ-gbakwunyere-cosine na-achịkwa, mana nghọta dị n'okpuru - na mmụba nke atụmatụ na-enyere aka ịgbanahụ mpaghara ọjọọ nke ọdịda ọdịda - na-agwa ịmalitegharị ọkụ (SGDR) na usoro nchịkọta nke na-ese foto n'ụdị ala ọ bụla. Na-atụ anya na ga-aga n'ihu na-agafe agafe n'etiti echiche cyclical na ndị na-eme mgbanwe, ndị na-ahazi nhazi onwe ha.
Mmejuputa n'ezie n'ụwa
fast.ai kwalitere amụma otu okirikiri dị ka ndabara maka ịzụ ngwa ngwa nhazi ọkwa onyonyo ka ọ dị elu nke ọma n'ime oge ole na ole.
Nnwale nso LR na-ebuli ọnụego elu karịa narị batches ole na ole iji were nkeji nkeji na max tupu ezigbo ọsọ.
Ịchịkọta foto foto na-echekwa ebe nlele ihe nlereanya na njedebe nke okirikiri ọ bụla, na-emepụta mkpokọta n'efu site n'otu ọsọ ọzụzụ.
Stochastic Gradient Descent na Warm Restarts (SGDR) na-atụgharị ọnụego ya kwa oge ka ọ bụrụ uru dị elu iji gbanarị minima dị nkọ.
Ihe ize ndụ & okporo ụzọ nche
Ịkwalite otu akara ngosi nwere ike zoo adịghị ike sistemụ sara mbara.
A na-eledakarị ihe akụrụngwa na ụgwọ ọrụ anya.
Ọdịiche nchekwa na nleba anya nwere ike itolite ka sistemu na-adịwanye mgbagwoju anya.
Map mmejuputa
Kọwaa latency, ịdịmma na ebumnuche ọnụ ahịa tupu mmejuputa ya.
Benchmark n'okpuru ibu dị adị na ọnọdụ data.
Nleba anya akụrụngwa maka mperi, ịkpafu na mmetụta onye ọrụ.
Kwadebe ụzọ nzaghachi azụghachi azụ na ihe omume tupu ịchachaa.
Nọgide na-eme nchọpụta
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Ntuziaka na-esote
Ịhazi ọnụ ọgụgụ mmụta
Ajụjụ a na-ajụkarị
What is Cyclical Learning Rates?
Ọnụego mmụta cyclical na-agbagharị ugboro ugboro n'ịmụ ihe n'ogo elu na ala n'etiti oke ala na elu kama naanị ire ere. Nke a na-emegiderịta onwe ya nwere ike ime ka nkwekọ dị ngwa ma na-enyere onye na-ebuli elu aka ịgbanarị minima mpaghara na isi ihe sadulu dị nkọ.
Kedu isi echiche na-agbagha ọnụego mmụta cyclical?
CLR kpachaara anya na-ebuli ọnụego ahụ ugboro ugboro, na-ajụ echiche ọdịnala na ọ ga-ererịrị naanị otu.
Kedu ihe kpatara ịbawanye ọnụego mmụta kwa oge nwere ike inye aka?
Mgbawa nke ọnụ ọgụgụ dị elu nwere ike ịchụpụ onye na-ebupụta ihe n'ebe dara ogbenye, dị nkọ ma ọ bụ n'isi ihe sadulu ka o wee chọta mpaghara ka mma.
Kedu ihe 'LR range test' na-eme?
Ọ na-agba ọsọ nkenke na ọnụ ọgụgụ na-arịwanye elu; usoro ọnwụ na-ekpughe ntakịrị ihe ezi uche dị na ya na nke kachasị iji mee ihe maka okirikiri.
N'ime amụma otu okirikiri, kedu ka ume na-esi emekarị n'ihe gbasara ọnụego mmụta?
Amụma otu okirikiri na-ebelata ike ka ọnụ ọgụgụ ahụ na-ebuli elu ma na-ebuli ya ka ọnụego na-adaba, nke na-agbakwụnye mmetụta na-agbanwe agbanwe.
Gịnị bụ 'snapshot ensembling' na gburugburu nke cyclical nhazi oge?
N'ihi na okirikiri nke ọ bụla na-adaba n'ime opekempe dị iche iche, ichekwa ebe nlele ndị ahụ na-ewepụta ọtụtụ ụdị dị iche iche site na otu ọsọ nke enwere ike ịgbakọta.